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branch of mathematics taking and transforming numbers into useful information for decision makers
Methods for processing and analyzing numbers
Method for helping reduce the uncertainty inherent in decision making |
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Descriptive and Inferential |
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Collecting, summarizing, and describing data |
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Drawing conclusions and/or making decisions concerning a population based only on sample data |
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a characteristic of an item or individual |
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different values associated with a variable |
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universally accepted meanings that are clear to all associated with an analysis |
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numerical measure that describes a characteristic of a population |
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Numerical measure that describes a characteristic of a sample |
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data collector is the one using the data for analysis *political survey *experiment *observed data |
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person analyzing the data, not collecting *analyzing census *data on internet |
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Categories of Data Sources |
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*data distributed by an organization or individual *designed experiment *survey *observational study |
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Categorical(qualitative) Variable |
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variables that have values that can only be placed into categories ("yes/no") |
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Numerical(quantitative) Variable |
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variables that represent quantities |
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finite or countable variable. example # of number children. 0,1,2... (counted items) |
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values from a range or interval. example weight,age, or voltage (measured characteristics) |
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Indicates frequency, amount, or percentage of items in a set of categories so that you can see the difference |
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length of bar or size of pie slice shows frequency or percentage for each category |
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bar shows each category, length represents the amount, frequency, or percentage of values falling into a category |
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Circle broken up into slices that represent categories. size of each slice varies according to percentages, higher percentage equals bigger slicer |
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simple way to see concentrations in data *leading digits (stems) *trailing digits (leaves) organizes data into groups(steams) so that values within each group(leaves) branch out to the right |
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summary table in which the data are arranged into numerically ordered classes |
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values that can be placed into categories ("yes and no") |
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tabular arrangement, intersections of rows and columns in Excel |
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produce numerical responses that arise from a measuring process |
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different values associated with a variable |
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collecting the date for variables |
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collecting, summarizing, presenting, and analyzing a set of data |
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numerical values that arise from a counting process |
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uses data collected from smaller group to draw conclusions about a larger group |
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values that represent quantities |
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universally accepted meanings that are clear to all associated with an analysis |
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numerical measure that describes a characteristic of a population |
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all items or individuals about which you want to draw a conclusion |
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when data collector is analyzing the data |
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file for programming information in Minitab |
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portion of population selected for analysis |
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variables that aren't studied by data collector |
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numerical measure that describes a characteristic of a sample |
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program designed to analyze data as accurate as possible |
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branch of mathematics that transforms numbers into useful information for decision makers |
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characteristic of an item or individual |
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spread sheets that store data |
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all items, sample is out of population |
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collection of data and inferential is making predictions |
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unnecessary adorments that convery no useful information |
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grouping data variables into certain intervals |
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halfway between lower and higher boundary of class |
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numerically ordered, data is arranged |
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categories of one variable written in rows and other variable written in columns |
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data sequence, lowest to highest |
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number of frequences divided by total number of values |
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highest value-lowest value |
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width of a class interval |
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range / number of classes |
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most common measure of central tendency. average |
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provides graphical representation based on s-number summary |
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extent to which all the data values group around a typical or central value |
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states that for any data set, percentage of values with distances of k standard deviations from mean must be: (1-1/k^2)x100% |
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coefficient of correlation |
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measures the relative strength of a linear relationship between two numerical values |
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relative measure of variation that is always expressed as a precentage |
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measures the strength of the linear relationship between two numerical values |
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valve located away from the mean |
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68% with 1 standard deviation 95% within 2 99.7% within 3 |
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Xsmallest,Qone,Qtwo,Qthree,Xlargest |
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difference between third and first quartiles |
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middle number in sequence |
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value that appears most often in data set |
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population standard deviation |
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measure of variation in a population |
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median, divides the smallest 25% from the larger 75% |
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smallest 75% from the larger 25% |
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split a set of data into 4 equal parts |
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largest value minus smallest value |
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summary measures resistant to outliers |
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pattern of the distribution of values from lowest value to the highest value |
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values are not symmetrical around mean |
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average scatter around mean |
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values distributed evenly above and below the mean |
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amount of dispersion away from central value |
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The standard score is
- [image]
- where:
- x is a raw score to be standardized;
- μ is the mean of the population;
- σ is the standard deviation of the population.
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where [image] the sample mean and [image] is the sample size. |
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Sample Standard Deviation |
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- [image]
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where [image] are the observed values of the sample items and [image] is the mean value of these observations. This correction (the use of N − 1 instead of N) is known as Bessel's correction. The reason for this correction is that s2 is an unbiased estimator for the variance σ2 of the underlying population, if that variance exists and the sample values are drawn independently with replacement. However, s is not an unbiased estimator for the standard deviation σ; it tends to underestimate the population standard deviation.
The term standard deviation of the sample is used for the uncorrected estimator (using N) while the term sample standard deviation is used for the corrected estimator (using N − 1). The denominator N − 1 is the number of degrees of freedom in the vector of residuals, [image].
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sum of values diveded by number of values
[image]. |
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[image][image][image][image] |
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bar chart without spaces, labeled by midpoints
[image] |
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bar shows each category
[image] |
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[image]
presents results of two categorical variables as cross tabulations
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Cumulative Percentage Distribution |
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provides a way of presenting information about the percentage of items that are less than a certain value[image] |
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variable of interest along x-axis and cumulative percentages along y-axis
[image] |
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[image]
summary table arranged into classes
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Relative Frequency Distribution |
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number of frequencies divided by total number of values
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use to examine possible relationships between two numerical values
[image] |
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values within each group branch out to right[image] |
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[image]
indicates frequency, amount, or percentage
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shows variables along a period of time
[image] |
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